What’s Up With S2F? — A Look At The Popular Bitcoin Model

·

The meteoric price rise of Bitcoin has captured global attention, sparking intense debate about its future trajectory. Will Bitcoin continue its historic ascent, or will growth slow—or even stall? One of the most discussed models attempting to answer this question is the stock-to-flow (S2F) model, introduced by the pseudonymous analyst PlanB. This framework posits that Bitcoin’s value is primarily driven by its increasing scarcity, with halving events reducing supply and thus fueling long-term price appreciation.

According to the S2F model, Bitcoin’s price follows a predictable path—roughly increasing tenfold every four years. This forecast has attracted a massive following, with millions tracking its projections. However, as popularity grows, so does scrutiny. Critics argue the model is flawed, while supporters maintain it remains a powerful tool for understanding Bitcoin’s scarcity-driven value.

So, where does the truth lie?

Understanding the Stock-to-Flow Model

At its core, the S2F model links Bitcoin’s market value to its scarcity. "Stock" refers to the total existing supply, while "flow" represents new supply entering the market annually. The ratio—stock divided by flow—measures how scarce an asset is. Gold, for example, has a high stock-to-flow ratio, contributing to its status as a store of value.

Bitcoin’s programmed halvings reduce the flow of new coins every four years, steadily increasing its stock-to-flow ratio. The model uses this dynamic to project future prices, suggesting a consistent upward trend: approximately $100,000 per BTC in this cycle, $1 million in the next, and beyond.

👉 Discover how scarcity influences digital asset valuation with real-time market insights.

But does this elegant theory hold up under scrutiny?

Debunking the Tautology Claim

One of the most repeated criticisms is that the S2F model is tautological—essentially claiming “stock equals stock,” making it mathematically invalid. Critics argue that because market cap (price × stock) appears on one side and stock-to-flow (stock ÷ flow) on the other, the equation is circular.

However, this misrepresents the model. While stock appears in both variables, the equation can be algebraically rearranged so that price is a function of stock and flow—not stock alone. The model doesn’t assume identity; it proposes a predictive relationship based on empirical data.

Moreover, whether one models market cap or price directly against stock-to-flow yields nearly identical results. The fit quality doesn’t meaningfully differ. So even if a tautology existed—which it doesn’t—the practical impact would be negligible.

Verdict: The tautology argument fails to invalidate the model.

Addressing Autocorrelation Concerns

Another critique centers on autocorrelation—the idea that today’s price depends heavily on yesterday’s, making statistical models unreliable. Some claim that when adjusted for this, the S2F model’s R-squared drops to zero, rendering it useless.

But this misunderstands the model’s intent. S2F isn’t designed to predict daily price movements. Its power lies in capturing long-term structural shifts driven by halvings—events that occur every four years. Small daily fluctuations in stock-to-flow are noise; the meaningful signal comes from large, infrequent supply shocks.

Expecting day-to-day causality between minor S2F changes and price is unrealistic. The model operates on macroeconomic principles, not high-frequency trading dynamics.

Verdict: Autocorrelation doesn’t negate S2F’s long-term predictive utility.

Ad Hominem Attacks: A Distraction

Some critiques focus not on the model, but on PlanB’s behavior—particularly his alleged blocking of critics on social media. While transparency and open debate are vital in research, personal conduct doesn’t invalidate a mathematical model.

I’ve publicly debated PlanB and exchanged privately with him—my experience has been respectful and constructive. Managing a 1.7 million-follower audience inevitably involves moderation choices. Regardless of individual actions, the model must stand on its own merits.

Verdict: Ad hominem attacks are irrelevant to model validity.

Cointegration: Overstated Importance?

A more technical argument involves cointegration—a statistical property suggesting a long-term equilibrium between variables. When studies found no cointegration between S2F and Bitcoin price, some declared the model dead.

But even Judea Pearl, a pioneer in causal inference, admitted he was unfamiliar with cointegration until recently—and cautioned that it doesn’t prove causality. At best, it hints at a possible relationship; at worst, its absence doesn’t rule one out.

The lack of cointegration may suggest weaknesses, but it’s far from a fatal flaw.

Verdict: Not a death blow—just a reminder to interpret statistical tools cautiously.

Frequently Asked Questions

Q: What is the stock-to-flow model in simple terms?
A: It’s a model that predicts Bitcoin’s price based on its scarcity. As new supply decreases every four years (halvings), the asset becomes more valuable over time.

Q: Has the S2F model been accurate so far?
A: It performed well in early cycles but has consistently overestimated prices in recent years. Bitcoin’s growth appears to be slowing—what experts call “diminishing returns.”

Q: Why do some people reject the S2F model?
A: Critics cite statistical issues like autocorrelation and lack of cointegration. Others argue it ignores market psychology, adoption rates, and macroeconomic factors.

Q: Is Bitcoin still scarce if S2F isn’t perfect?
A: Absolutely. Scarcity is built into Bitcoin’s code—only 21 million will ever exist. The debate is about how directly that scarcity translates into price.

Q: Are there better alternatives to S2F?
A: Yes. Models like the power-law corridor of growth account for slowing appreciation rates and fit historical data more closely.

👉 Explore data-driven crypto models that adapt to real-world market behavior.

An Empirical Challenge: Diminishing Returns

In 2019, I introduced the power-law corridor of growth model, based on Giovanni Santostasi’s observation that Bitcoin’s price follows a logarithmic trend—meaning growth slows over time.

Early on, Bitcoin’s price increased tenfold in about a year. Now, it takes several years. This diminishing returns pattern contradicts S2F’s assumption of steady exponential growth.

My 2019 forecast—a $100K BTC between 2021–2028 and $1M between 2028–2037—remains on track. The S2F model, meanwhile, predicted $100K much earlier and continues to project steeper climbs.

Historical data supports slowing growth. The S2F multiple, tracked by @s2fmultiple, shows Bitcoin frequently trading below S2F expectations post-2015—further evidence the model runs too hot.

👉 See how real-time data compares to long-term crypto forecasts.

Final Thoughts

The S2F model has sparked valuable discussion about scarcity and value. While it’s been unfairly attacked on some fronts (tautology, ad hominem), its core flaw is empirical: it assumes constant growth without diminishing returns—a pattern unsupported by data.

That doesn’t mean Bitcoin’s future is dim. On the contrary, I remain bullish—just not unrealistically so. A $1M Bitcoin is plausible, but likely later than S2F suggests.

Let’s focus on models grounded in observable trends—not wishful extrapolations.

Core Keywords: